An elevator adaptive shunt method with a combined layer strategy powered by an emergency power supply

Abstract

The present invention belongs to the technical field of adaptive dynamic programming, and proposes an adaptive shunt method for elevators with a merged floor strategy powered by an emergency power supply. Specifically: First, identify the energy storage power supply mode by monitoring the elevator voltage fluctuation. When the energy storage power supply mode is triggered, form merged floors by aggregating consecutive high-demand areas based on the destination floor data. Then, determine whether there is overloading in the execution service range according to the elevator load. Finally, when overloading occurs, reassign the service range for the elevator group. By adaptively establishing merged floors according to time periods, the merging quality of the merged floors is improved, so that while the docking rate is reduced during the application of the merged floor strategy, the no-load rate can also be effectively reduced. Adjust the service range for the problem of overloading of individual elevators during the application of the merged floor strategy, and the power consumption balance between elevators makes the cooperation between the parallel energy storage power supplies more stable.

Description

Technical Field

[0001] The invention belongs to the technical field of adaptive dynamic programming, and in particular relates to an adaptive flow diversion method for an elevator with a merged layer strategy powered by an emergency power supply. Background Art

[0002] In the normal operation of the elevator system, the elevator usually relies on a direct connection to the power grid to obtain a stable power supply. However, in the face of power outages, system failures or other emergencies, the elevator must switch to energy storage batteries for power supply, which puts higher requirements on the energy scheduling and optimization of the diversion system. In the existing diversion strategy, by setting fixed floors as the boundaries of the service area, the elevator divides the functions between different floors, thereby effectively simplifying the complexity of scheduling decisions. On this basis, the merging layer strategy can greatly improve the durability of the elevator power supply. The merging layer strategy refers to merging several consecutive target floors into one target floor, and transporting passengers going to these floors to one of the merged floors, which not only optimizes the scheduling efficiency, but also enhances the continuity and stability of power supply when there is a lack of external power input. However, on the one hand, the existing merging layer strategy is usually implemented in a fixed proportion, for example, every two floors are merged into one merged layer. The disadvantage of this traditional merging method is that the parking rate is still relatively high, so the power consumption is limited, and this solidified mode cannot be adapted according to the actual elevator demand, which makes some merged layers have serious problems of empty transportation. On the other hand, there is a load imbalance problem between elevators in the merged layer strategy. Although merged layer transportation effectively reduces the stop rate, the weight density of each elevator transported per unit time increases accordingly. Especially when the elevator service range is in the floor interval with high transportation demand or during peak hours, the load pressure is huge. This long-term high-load operation requires the battery to provide higher power output, causing the battery temperature to rise and accelerate its degradation and attenuation. As the discharge depth of the battery gradually increases, the potential difference of the battery gradually decreases, resulting in the elevator being unable to maintain stable power output under high load, thereby affecting the operating stability of the elevator and the stability of the microgrid. Summary of the invention

[0003] The purpose of the present invention is to propose an adaptive diversion method for elevators with a merged floor strategy powered by an emergency power supply to solve one or more technical problems existing in the prior art and at least provide a beneficial choice or create conditions.

[0004] In order to achieve the above object, according to one aspect of the present invention, a method for adaptive traffic diversion of an elevator with a merged floor strategy powered by an emergency power supply is provided, the method comprising the following steps:

[0005] Identify the energy storage power supply mode by monitoring the elevator voltage fluctuation; after triggering the energy storage power supply mode, whenever the elevator stops at the first floor, dynamically form a merged floor by aggregating consecutive high-demand areas based on the destination floor data; determine whether there is an overloaded condition in the execution service range of the elevator according to the elevator load; when there is an overloaded condition, reassign the service range for the elevator group.

[0006] Further, the method for identifying the energy storage power supply mode by monitoring the elevator voltage fluctuation is as follows: Use a voltage sensor to collect the voltage data of the elevator in real time, and the voltage data measurement frequency ranges from 1 to 50 milliseconds per time; Set a dynamic window of 2 to 10 minutes, with a default value of 5 minutes; Obtain the average value of each voltage data within the dynamic window at each moment and record it as the window voltage, fit the window voltages through a curve and obtain the change rate of the curve at each moment and record it as the average voltage change rate, where the change rate of the curve is obtained through the first derivative; If the average voltage change rate is greater than the preset voltage change threshold, it is identified that the energy storage power supply mode is turned on.

[0007] This method reduces the possible instantaneous interference of single sampling through the dynamic window, while retaining the short-term trend changes and reducing the risk of false triggering. The voltage data generally serves the monitoring of the elevator power supply status in the long term, and there is no need to arrange additional test instruments. Usually, the value range of the voltage change threshold is 2.5V / s - 10V / s; In the process of selecting the voltage change threshold, it should be considered that if it is just a normal UPS switch, it is set to 2.5V / s - 5V / s, the sudden switch for supercapacitor protection is set to 5.0 V / s - 7.0 V / s, and if it is the direct connection to the diesel generator mode, it is 5.0V / s - 10.0V / s.

[0008] Further, or, the method for identifying the energy storage power supply mode by monitoring the elevator voltage fluctuation is as follows: Use a voltage sensor to collect the voltage data of the elevator in real time, set a dynamic window of 2 to 10 minutes, and when the fluctuation range of the voltage data within the dynamic window exceeds ±5% - ±10%, it is identified that the energy storage power supply mode is turned on.

[0009] This method is applicable to simple PLC circuits of devices with limited computing resources.

[0010] Further, when the energy storage power supply mode is triggered, the method for aggregating consecutive high-demand areas into a merged floor based on the destination floor data is as follows: Intercept the destination floor historical data set from the destination floor data in real time; The destination floor historical data set consists of several destination floor historical data records, and each destination floor historical data record includes the real-time timestamp distance and the destination floor, and the real-time timestamp distance ranges from 10 to 60 minutes;

[0011] The DBSCAN clustering method is used to cluster the historical dataset of the destination floors. After filtering the clustering results through the LOF algorithm, several clusters are obtained. The cluster with the largest number of elements within the cluster is the target cluster. All target floors are identified from the target cluster, and the set of any consecutive several target floors is denoted as a merged floor.

[0012] Here, the destination floor data is a data record consisting of a timestamp and the destination floor, and these data records are limited to the destination floor data records starting from the first floor or the basement floor. The basement floor usually refers to the main floor where the elevator transports external passengers to different floors in the building.

[0013] The real-time timestamp distance refers to the time gap between the timestamp in the destination floor data record and the current moment; the reading range of the timestamp is 24 hours; the time gap includes positive and negative values.

[0014] The LOF algorithm is a local outlier factor identification algorithm;

[0015] The upper limit of the merged floor is preset to 2 - 6 floors. When the number of merged floors exceeds the upper limit of the merged floor, the merged floor is split into 2 merged floors. By default, the elevator transports passengers from the first floor or the basement floor to the floor with the highest target floor in the merged floor.

[0016] The merged floor means that adjacent high-demand floors are merged into one stop floor, effectively reducing the number of elevator starts and stops and reducing energy consumption. The reduction in the number of starts and stops is beneficial to maintaining the long-term operating state of the energy storage power supply and extending the recovery time of the energy storage power supply.

[0017] Passengers departing from the first floor select the target floor in the elevator lobby. The display in the elevator lobby diverts the passengers, that is, the target floor guides the passengers to the corresponding elevator.

[0018] The construction of the merged floor is based on a density-based clustering method, so as to effectively extract the regularity of the target floor requirements of passengers during a specific period, reduce the sensitivity of floors with a lower docking demand density, and then reasonably allocate different passengers to the corresponding elevators, making the operating paths of each elevator more concentrated, reducing the docking rate and also suppressing the empty load rate.

[0019] Furthermore, the method for judging whether the execution service range of the elevator is overloaded according to the elevator load is as follows: The preset feedback interval is 2 seconds to 20 seconds, and each time point corresponding to the feedback interval is denoted as a monitoring point. The elevator load includes the power consumption value and the power peak value obtained once at each monitoring point, where the power consumption value is the average power consumption within the dynamic window corresponding to the monitoring point.

[0020] The dynamic window corresponding to the monitoring point refers to the time period in the reverse time direction of the monitoring point, with a value range of 2 to 5 minutes;

[0021] The calculation method of the average power consumption is the ratio of the total power consumption within the dynamic window to the time size of the dynamic window.

[0022] Furthermore, the method for judging whether the execution service range of the elevator is overloaded according to the elevator load is as follows:

[0023] For the power consumption value and power peak dataset of the monitoring point, dynamic normalization processing is performed through a multi-dimensional quantile discretization framework. The specific process is as follows:

[0024] Adopt a quantile-driven discretization strategy to divide the parameter space of power consumption and power peak into four interval units respectively, and ensure that the probability density distribution of each interval satisfies the non-uniformity constraint; among them, the four obtained interval units do not necessarily show symmetry; the interval units are briefly recorded as units;

[0025] Define the two polar boundaries of extracting the internal power consumption value of any interval unit as the range amplitude;

[0026] Quantify the discrete intensity of the power consumption fluctuation within the unit through the range amplitude, that is, the difference between the maximum power consumption observation value and the minimum power consumption observation value within the unit; among them, the identified two polar boundaries refer to the maximum value and the minimum value, so the range amplitude is used as a scalar measure ∆ of the energy consumption disorder within the unit j ;

[0027] Execute the extraction of bimodal statistics for the interval unit: the median value of the power consumption value is used as a robust central estimator E of the energy consumption distribution within the unit j ; the median value of the power peak is used as a typical characterization quantity P of the load intensity within the unit j ;

[0028] Construct a probability mass function of the power consumption weight based on the global contribution ratio of the range amplitude: the power consumption weight of the unit is the normalized ratio of its range amplitude to the sum of the range amplitudes of all units; that is, the power consumption weight of the unit is the ratio of its range amplitude to the sum of the power consumption weights of all interval units, and the obtained ratios of each interval unit are normalized;

[0029] The calculation process of the power consumption weight of the required unit is actually to accurately capture the load fluctuation trend. When the elevator starts and stops frequently or the load density fluctuates greatly during operation, the electrochemical reaction inside the battery shows rapid periodic changes. The power consumption weight captures the range of energy consumption in the interval through the quantile discretization technology. This range represents the rapid change degree of the elevator load from low to high. When the power consumption weight is high, it implies that the elevator has experienced a large power fluctuation in a short period of time. This load fluctuation is directly reflected in the instantaneous power output of the battery. Frequent and drastic power fluctuations lead to accelerated chemical reaction rates inside the battery, and the diffusion and exchange rates of electrolyte ions on the electrode surface change frequently, causing an increase in internal resistance and generating additional Joule heat, causing the local temperature of the battery to rise rapidly. For a fixed four-story trip condition, the energy consumption of the elevator may vary from 14kJ to 270kJ under different conditions. The non-uniform performance of the energy consumption distribution of the elevator further proves that the internal structure of the battery deteriorates rapidly and the battery capacity decays rapidly under time accumulation. Therefore, this trend needs to be involved in identifying the risk of battery degradation through the curve function constructed later.

[0030] At the same time, the construction of power weight depends on the relative strength of the median power peak value within the unit, that is, the ratio of the median power peak value of each unit to the sum of the median power peak values ​​of all units, so as to map the heterogeneous impact of power distribution on system load;

[0031] The current fluctuation of the motor during operation is directly affected by the load. Generally speaking, when the load of the elevator increases, the rotor induced current increases, the torque output increases and the power increases. Therefore, when individual elevators are in the high power range for a long time while the load of other elevators is relatively low, it means that there is a high-low power load difference in the operation process, which further causes the power supply to reach the critical state of deep discharge of the battery in advance, causing the power supply potential to be significantly reduced and unable to stably output the required power. Therefore, it is necessary to use the power weight to construct the curve function to further identify the risk of battery degradation caused by the existence of this load imbalance.

[0032] The hyperbolic tangent function is constructed by power weight and power consumption weight to obtain the imbalance factor. Through the dynamic normalization mechanism driven by the segmented median value, this method can eliminate the dimensional difference while retaining the local nonlinear characteristics of the elevator load. Based on the design of the hyperbolic tangent function, the implicit interference of the data of high-power consumption and low-power equipment is suppressed, and the system's data sensitivity to load mutation scenarios is enhanced.

[0033] The core principle of using the hyperbolic tangent function to quantify the degree of deviation between the power weight and the power consumption weight is that the hyperbolic tangent function changes little in the area close to 0, but changes steeply at extreme values, which helps to avoid misjudgment within the normal range. When the power weight or power consumption weight exceeds the set threshold, the abnormal signal can be quickly amplified, making the impact of load abnormality or dust accumulation easier to identify.

[0034] The set of all imbalance factors between the last elevator maintenance and the current one is recorded as the imbalance factor set. If the imbalance factors of all elevators meet the Z-Score ≥ 2.5 in the corresponding previous imbalance factor set, it is determined that the elevator is overloaded, and the overloaded elevator is pointed to the elevator corresponding to the maximum value in the imbalance factor set. The dynamic window method of the imbalance factor set is to limit its data history to the current 48 hours, so as to prevent the problem of sensitivity failure caused by too long maintenance cycle.

[0035] The current moment inherits the imbalance factor of the current monitoring point.

[0036] Here, the imbalance factor is measured through dynamic monitoring of the elevator load, so it can effectively quantify the excess characteristics of the elevator load process in actual operation. However, since the quantification process is directly related to the interval unit in which it is located, the analysis of the timing angle is defective, especially the data with a sudden increase in timing in a short period of time cannot be identified with high sensitivity. In order to solve this defect and reduce the sensitivity problem caused by this defect in timing angle analysis, another method for measuring the imbalance factor is provided.

[0037] The Z-Score threshold recognition method recommends the use of a dynamic window method because it can avoid data failure caused by battery capacity degradation during long-term operation. That is, the longer the battery is used, the greater the chance of judging that the elevator is overloaded. If the battery is a rechargeable working type, such as diesel power generation or solar power storage to supplement the power supply, a dynamic window must be defined. If the battery cannot be dynamically replenished, there is no need for dynamic recognition because its short operating cycle has little effect on the sensitivity of abnormal recognition.

[0038] Further, the method for judging whether the service range of the elevator is overloaded according to the elevator load is:

[0039] In order to further deepen the real-time observation and judgment mechanism of overload phenomenon in the elevator loading process, this study proposed a load discrimination model based on time dynamic changes.

[0040] The independent variables σ are power consumption and peak power. T , σ P Based on, define the parameter load discrete level R TP , the parameter load discrete level is used to characterize the intrinsic reflection of the synergistic relationship between power consumption and power peak on the dynamic sensitivity of system load. In particular, by examining the change behavior of load discrete level over time, the first load discrimination model is constructed:

[0041] ;

[0042] The first load discrimination model synthesizes the power consumption value and the time derivative of the power peak, so as to express the degree of coupling effect of the non-linear dynamic characteristics of the interaction between power consumption and power peak in the time dimension. Its principle lies in capturing the impact of the mismatch or synergy effect between power consumption and power peak on the load dynamics in the elevator system; where σ P 2 Ensures that the rate of change of R TP is related to the absolute magnitude of the power peak, avoiding scale imbalance caused by excessive differences in the power peak amplitude; dσ T / dt and σ P vary in the same direction, and the mathematical contribution is positive, indicating that the load may be under increasing pressure; while σ T and dσ P vary in the opposite direction, and the mathematical contribution is positive. As a relief mechanism for the degree of increasing critical pressure, it is the ability performance of maintaining the high-load operation state. Therefore, when (dσ T >0), the power consumption increases rapidly while the power peak remains high (σ P is large), the problem pointed to is that the elevator system is bearing an abnormal load, resulting in an increase in the rate of change of R TP . On the contrary, it may reflect that the system enters an inefficient operation state, which also affects the load dynamics. This coupling effect in the time dimension is the source manifestation of the non-linear dynamic characteristics in the operation of the elevator system.

[0043] Based on the above parameters, by introducing the dynamic evolution behavior of the imbalance factor VIDX, a core differential equation describing the influence of the elevator load array on the imbalance factor is constructed, denoted as the second load discrimination model:

[0044] ；

[0045] Among them, the quantization parameter k 1 represents the direct sensitivity caused by the power consumption value, and its action intensity is determined by the specific dependence of the elevator group system on the change of the power consumption value. Combining dσ T / dt is to reflect the short-term sudden increase behavior in the change of power consumption data, including the power consumption changes in heavy loads and frequent starts and stops in the elevator. Therefore, it can be used to capture the direct contribution of power consumption changes to elevator load imbalance; the quantization parameter k 2 represents the indirect perturbation caused by the change rate of the power peak, reflecting the fatigue strength of the system under different power peak conditions. Combining dσ P / dt reflects whether the dynamic demand of the elevator system power tends to be stable. The larger the value, the more unstable the system operation state is, and it is easy to cause fatigue accumulation of mechanical components; the quantization parameter k 3 represents the composite effect of the load discrete level on the system, used to describe the weight effect of the coupling dynamics of power consumption and power peak, combined with dRTP / dt captures the composite influence degree of the dynamic changes in the co - calculation of power consumption and power peak on the imbalance factor. The larger the value, the stronger the unevenness of the load distribution in the coupling dynamic, and the worse the stability of the elevator load's power demand.

[0046] k 1 , k 2 and k 3 are preset weight values, with a value range of (0, 1], and the default value is 1.

[0047] The set of all imbalance factors between the last maintenance of the elevator and the current time is denoted as the imbalance factor set. If for all elevators, when the imbalance factor in the corresponding previous imbalance factor set meets Z - Score≥2.5, it is determined that there is an elevator with excessive load, and the elevator with excessive load is pointed to the elevator corresponding to the maximum value in the imbalance factor set.

[0048] Further, when there is excessive load, the method for re - distributing the service range for the elevator group is as follows: Select and define the elevator with excessive load as the re - planned elevator. Its service range is several consecutive floors, which is denoted as the service floor set, and the highest floor in the service floor set is removed.

[0049] If after the removal operation, the removed floor is not within the service range of any elevator, and there are other elevators whose service range is above this removed floor, then add the removed floor to the service elevator corresponding to its upper floor.

[0050] Preferably, in the present invention, for all undefined variables, if there is no clear definition, they can be artificial - set thresholds.

[0051] The present invention also provides a merged - floor - strategy elevator adaptive shunt system powered by an emergency power supply. The merged - floor - strategy elevator adaptive shunt system powered by an emergency power supply includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps in the method of the merged - floor - strategy elevator adaptive shunt powered by an emergency power supply. The merged - floor - strategy elevator adaptive shunt system powered by an emergency power supply can run on computing devices such as desktop computers, laptop computers, palmtop computers, and cloud data centers. The operable system may include, but is not limited to, a processor, a memory, and a server cluster. The processor executes the computer program and runs in the following units of the system:

[0052] The energy - storage power - supply identification unit is used to identify the energy - storage power - supply mode by monitoring the elevator voltage fluctuation;

[0053] The merged floor planning unit is used to form a merged floor by aggregating continuous high-demand areas based on destination floor data when the energy storage power supply mode is triggered.

[0054] The overloaded load identification unit is used to determine whether the execution service range of an elevator is overloaded according to the elevator load.

[0055] The service range adjustment unit is used to reassign the service range for the elevator group when overloading occurs.

[0056] The beneficial effects of the present invention are as follows: The present invention provides an emergency power supply-based merged floor strategy elevator adaptive diversion method. On the one hand, by adaptively establishing the merged floor according to time periods, the merging quality of the merged floor is improved, so that while the docking rate is reduced during the application of the merged floor strategy, the no-load rate can also be effectively reduced. On the other hand, the service range is adjusted for the problem of overloading of individual elevators during the application of the merged floor strategy, thereby reducing the working pressure of high-load elevators. The power consumption balance between elevators makes the cooperation between parallel energy storage power supplies more stable, reduces the probability of sudden load impacts, and thus enhances the power supply stability and sustainability of the microgrid. Description of the Drawings

[0057] By elaborating on the embodiments shown in conjunction with the drawings, the above and other features of the present invention will become more obvious. The same reference numerals in the drawings of the present invention represent the same or similar elements. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts. In the drawings:

[0058] Figure 1 Shown is a flowchart of an emergency power supply-based merged floor strategy elevator adaptive diversion method.

[0059] Figure 2 Shown is a structural diagram of an emergency power supply-based merged floor strategy elevator adaptive diversion system. Detailed Embodiments

[0060] The following will clearly and completely describe the concept, specific structure, and technical effects generated by the present invention in combination with embodiments and drawings to fully understand the purpose, solution, and effects of the present invention. It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other.

[0061] As Figure 1 Shown is a flowchart of an emergency power supply-based merged floor strategy elevator adaptive diversion method. The following will be combined with Figure 1To describe an emergency power supply - powered combined - layer strategy elevator adaptive diversion method according to an embodiment of the present invention, the method includes the following steps:

[0062] Identify the energy storage power supply mode by monitoring the elevator voltage fluctuation; after triggering the energy storage power supply mode, whenever the elevator stops at the first floor, dynamically form combined floors by aggregating consecutive high - demand areas based on the destination floor data; judge whether the service range of the elevator has an excessive load according to the elevator load; when there is an excessive load, re - allocate the service range for the elevator group.

[0063] Further, the method of identifying the energy storage power supply mode by monitoring the elevator voltage fluctuation is as follows: Use a voltage sensor to collect the voltage data of the elevator in real - time, and the voltage data measurement frequency ranges from 50 milliseconds per time; set a dynamic window of 5 minutes; obtain the average value of each voltage data within the dynamic window at each moment and record it as the window voltage, fit each window voltage through curve fitting and obtain the change rate of the curve at each moment and record it as the average voltage change rate, where the change rate of the curve is obtained through the first - order derivative; if the average voltage change rate is greater than the preset electrical change threshold, it is identified that the energy storage power supply mode is turned on.

[0064] Fit the window voltage using the least - squares method to obtain the curve V(t), then the average voltage change rate is: V’(t) = dV / dt, and the average voltage change rate represents the change rate of voltage with time, and the electrical change threshold is 5.0 V / s;

[0065] Further, when the energy storage power supply mode is triggered, the method of aggregating consecutive high - demand areas based on the destination floor data to form combined floors is as follows: Intercept the destination floor historical data set from the destination floor data in real - time; the destination floor historical data set consists of several destination floor historical data records, and each destination floor historical data record includes the real - time timestamp distance and the destination floor, and the real - time timestamp distance ranges from 20 minutes;

[0066] Use the DBSCAN clustering method to cluster the destination floor historical data set, filter the clustering results through the LOF algorithm to obtain several clusters, the cluster with the largest number of elements within the cluster is the target cluster, identify all target floors from the target cluster, and record the set of any consecutive several target floors as a combined floor.

[0067] The upper limit of the combined floor is preset to 4 floors. When the number of combined floors exceeds the upper limit of the combined floor, the combined floor is divided into 2 combined floors.

[0068] Passengers departing from the first floor select the destination floor in the elevator lobby, and the display in the elevator lobby diverts the passengers, that is, the destination floor guides the passengers to the corresponding elevator.

[0069] In an embodiment, the floors are represented by F plus a number. The total number of floors is 21. The elevator identification merged floors are F{4, 5}, F{9, 10}, and F{18, 19, 20} respectively. F{4, 5} means that the 4th and 5th floors are constructed as a merged floor, and the same applies to F{9, 10} and F{18, 19, 20}. Therefore, when passengers select the 4th floor, they will actually be carried to the 5th floor and then reach the 4th floor by stairs. When passengers select the 9th floor, they will actually be carried to the 10th floor and then reach the 9th floor by stairs. When passengers select the 18th or 19th floor, they will actually be carried to the 20th floor and then reach the 18th and 19th floors by stairs.

[0070] Further, the method for judging whether there is overloading in the execution service range according to the elevator load is as follows: The preset feedback interval is 5 seconds, and each time point corresponding to the feedback interval is recorded as a monitoring point. The elevator load includes the power consumption value and the power peak value obtained once at each monitoring point. The power consumption value is the average power consumption within the dynamic window corresponding to the monitoring point.

[0071] The dynamic window corresponding to the monitoring point refers to the time period with a value of 2 minutes in the reverse time direction of the monitoring point. The calculation method of the average power consumption is the ratio of the total power consumption within the dynamic window to the time size of the dynamic window.

[0072] Further, the method for judging whether there is overloading in the execution service range according to the elevator load is as follows: For the data set of the power consumption value and the power peak value at the monitoring point, dynamic normalization processing is performed through a multi-dimensional quantile discretization framework. The specific process is as follows:

[0073] Adopt a quantile-driven discretization strategy to divide the parameter space of power consumption and power peak value into four interval units respectively, and ensure that the probability density distribution of each interval satisfies the non-uniformity constraint. Among them, the four obtained interval units do not necessarily show symmetry. The interval unit is briefly recorded as a unit.

[0074] Define any interval unit and extract the two-pole boundary of the internal power consumption value as the range amplitude.

[0075] Quantify the discrete intensity of the power consumption fluctuation within the unit through the range amplitude, that is, the difference between the maximum power consumption observation value and the minimum power consumption observation value within the unit. The identified two-pole boundary refers to the maximum value and the minimum value.

[0076] Perform bimodal statistic extraction on the interval unit: The median value of the power consumption value is used as the robust central estimator E of the energy consumption distribution within the unit j ; The median value of the power peak value is used as the typical characterization quantity P of the load intensity within the unit j ; The range amplitude is used as the scalar measure ∆ of the energy consumption disorder within the unit j ;

[0077] Construct the probability mass function of the power consumption weight based on the global contribution ratio of the range amplitude: The power consumption weight of a unit is the normalized ratio of its range amplitude to the sum of the range amplitudes of all units.

[0078] Meanwhile, the construction of the power weight depends on the relative intensity of the median value of the power peak within the unit, that is, the ratio of the median value of the power peak of each unit to the sum of the median values of the power peaks of all units.

[0079] Obtain the imbalance factor through the hyperbolic tangent function, and the mathematical expression of the imbalance factor can be:

[0080] ;

[0081] where i is the monitoring point serial number; j is the interval unit serial number; i(j) represents the interval unit corresponding to monitoring point i; n is the number of monitoring points; tanh(·) is the hyperbolic tangent function, which is used to compress the influence of extreme values. Through the dynamic normalization mechanism driven by the segmented median value, this method eliminates the dimension difference while retaining the local non-linear characteristics of the elevator load; here, the calculation principle of the imbalance factor is that the hyperbolic tangent function in the numerator is the power consumption term, and the rest of the numerator is the power term. The power consumption term is used to amplify the sensitivity of load mutation, and the larger the value, the stronger the local power consumption change degree. The power term is to compare the local relative deviation value with the global contribution weight. The larger the power term, the greater the deviation degree of the power consumption from the normal working range in the short term. The right end of the formula is the global energy efficiency factor, which drives the VIDX value to tend to the steady-state value 1 through the total energy consumption and total power. When the VIDX value of the normal load tends to be stable, the VIDX value of the overload significantly exceeds the steady state, so as to monitor the VIDX anomaly.

[0082] The set of all imbalance factors between the last maintenance of the elevator and the current time is denoted as the imbalance factor set. If the imbalance factors of all elevators meet Z-Score≥2.5 in the corresponding previous imbalance factor set, it is determined that there is an elevator with excessive load, and the elevator with excessive load is pointed to the elevator corresponding to the maximum value in the imbalance factor set.

[0083] Among them, the imbalance factor at the current moment inherits the imbalance factor of the current monitoring point.

[0084] Furthermore, the method for judging whether there is excessive load in the execution service range according to the elevator load is:

[0085] To further deepen the real-time observation and judgment mechanism of the excessive load phenomenon during the elevator load process, this study proposes a load discrimination model based on time dynamic changes.

[0086] Taking the independent variables σ of the power consumption value and the power peak T , σ P as the basis, define the parameter load discrete level R TP, the parameter load discrete level is used to characterize the internal reflection of the synergistic relationship between power consumption and power peak on the dynamic sensitivity of the system load. In particular, by examining the variation behavior of the load discrete level over time, a first load discrimination model is constructed:

[0087] ；

[0088] Based on the model constructed with the above parameters, by introducing the dynamic evolution behavior of the imbalance factor VIDX, a core differential equation describing the influence of the elevator load array on the imbalance factor is constructed, denoted as the second load discrimination model:

[0089] ；

[0090] Among them, the quantization parameter k 1 represents the direct sensitivity caused by the power consumption value, and its intensity of action is determined by the specific dependence of the elevator group system on the change of the power consumption value; the quantization parameter k 2 represents the indirect perturbation caused by the change rate of the power peak, reflecting the fatigue strength of the system under different power peak conditions; the quantization parameter k 3 represents the composite influence of the load discrete level on the system, used to describe the weight effect of the coupling dynamics of power consumption and power peak, and the values of k1, k2 and k3 are 1;

[0091] The set of all imbalance factors between the last maintenance of the elevator and the current is denoted as the imbalance factor set. If all elevators meet the condition of Z-Score≥2.5 in the corresponding previous imbalance factor set, it is determined that there is an elevator with excessive load, and the elevator with excessive load is pointed to the elevator corresponding to the maximum value in the imbalance factor set.

[0092] To further reduce the influence of the gradual attenuation of the system recovery ability with the fluctuation intensity, the second load discrimination model can be optimized into the third load discrimination model: ; among them, the self-recovery term -VIDXe in the third load discrimination model -I is used to describe the behavior of the system recovery ability gradually decaying with the fluctuation intensity under high fluctuation states; among them, I is a scalar quantization parameter representing the intensity of the influence of the system under the comprehensive action of the changes in power consumption, power peak and their coupling relationship, and the specific definition is: ; It should be noted that as the severity of the load discrete level fluctuation increases, the change rate of the imbalance factor VIDX increases significantly. At this time, it indicates that the self-recovery ability of the system shows a significant downward trend, and the sensitivity of the imbalance factor to the combined layer elevator demand gradually increases.

[0093] Further, the method for reassigning the service scope for the elevator group when overloading occurs is as follows: Select and define the elevator with overloading as the elevator to be re-planned. Its service scope is several consecutive floors, which is denoted as the service floor set, and the highest floor in the service floor set is removed.

[0094] In the embodiment, the floors are represented by F plus numbers. The service floor set of elevator A is the set composed of F2 - F12, where F2 - F12 refers to each consecutive floor between F2 and F12; the service scope of elevator B is the set composed of F10 - F21; when elevator A is marked as the elevator to be re-planned, F12, as the highest floor in the service floor set, is removed, so that the service floor set of elevator A is updated to F2 - F11; when elevator B is marked as the elevator to be re-planned, F21, as the highest floor in the service floor set, is removed, so that the service floor set of elevator A is updated to F10 - F20; since F21 is removed, the passengers who need to reach the 21st floor can only be delivered to the 20th floor and reach the 21st floor through the stairs. The occurrence probability of overloading will converge as the number of times of re-planning the elevator during the power supply operation increases, so that the service scopes of the elevators in the elevator group tend to be stable.

[0095] If the removed floor is not within the service scope of any elevator after the removal behavior, and there is the service scope of other elevators above this removed floor, then add the removed floor to the service elevator corresponding to its upper floor. Assume that the service floor set of elevator A is the set composed of F2 - F10, and the service scope of elevator B is the set composed of F11 - F21. When elevator A is marked as the elevator to be re-planned, F10, as the highest floor in the service floor set, is removed, so that the service floor set of elevator A is updated to F2 - F9, and the service scope of elevator B is changed to F10 - F21.

[0096] An emergency power supply-powered combined floor strategy elevator adaptive diversion system provided by the embodiment of the present invention, as Figure 2 shown in the structure diagram of an emergency power supply-powered combined floor strategy elevator adaptive diversion system of the present invention. The emergency power supply-powered combined floor strategy elevator adaptive diversion system of this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the embodiment of the above-mentioned emergency power supply-powered combined floor strategy elevator adaptive diversion method are implemented.

[0097] The system includes: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it runs in the following units of the system:

[0098] The energy storage power supply identification unit is used to identify the energy storage power supply mode by monitoring the elevator voltage fluctuation;

[0099] The merged floor planning unit is used to form a merged floor by aggregating continuous high-demand areas based on the destination floor data when the energy storage power supply mode is triggered;

[0100] The overloading identification unit is used to determine whether overloading occurs in the execution service range of the elevator according to the elevator load;

[0101] The service range adjustment unit is used to reassign the service range for the elevator group when overloading occurs.

[0102] The above-mentioned merged floor strategy elevator adaptive diversion system powered by emergency power supply can run on computing devices such as desktop computers, laptop computers, palmtop computers and cloud servers. The above-mentioned merged floor strategy elevator adaptive diversion system powered by emergency power supply, the operable system may include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the above examples are only examples of the merged floor strategy elevator adaptive diversion system powered by emergency power supply, and do not constitute a limitation on the merged floor strategy elevator adaptive diversion system powered by emergency power supply. It may include more or fewer components than the examples, or combine certain components, or different components. For example, the above-mentioned merged floor strategy elevator adaptive diversion system powered by emergency power supply may also include input / output devices, network access devices, buses, etc.

[0103] The so-called processor may be a central processing unit (CPU), or may also be other general-purpose processors, digital signal processors (DSPs), application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The processor is the control center of the operating system of the above-mentioned merged floor strategy elevator adaptive diversion system powered by emergency power supply, and uses various interfaces and lines to connect all parts of the operable system of the above-mentioned merged floor strategy elevator adaptive diversion system powered by emergency power supply.

[0104] The memory can be used to store the computer programs and / or modules. By running or executing the computer programs and / or modules stored in the memory, and invoking the data stored in the memory, the processor realizes various functions of the elevator adaptive shunt system with an emergency power supply-based merging layer strategy. The memory may mainly include a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, phone book, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a Flash Card, at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0105] Although the description of the present invention has been quite detailed and has particularly described several of the embodiments, it is not intended to be limited to any of these details or embodiments or any particular embodiment, so as to effectively cover the intended scope of the present invention. In addition, the present invention is described above in terms of embodiments foreseeable by the inventors for the purpose of providing a useful description, and non-substantive modifications to the present invention that are not currently foreseeable may still represent equivalent modifications of the present invention.

Claims

1. An adaptive traffic diversion method for elevators with a merged floor strategy powered by an emergency power supply, characterized in that: The method comprises the following steps: identifying the energy storage power supply mode by monitoring the voltage fluctuation of the elevator; after the energy storage power supply mode is triggered, each time the elevator stops at the first floor, dynamically forming a merged layer by aggregating continuous high-demand areas through the destination floor data; judging whether the service range executed by the elevator is overloaded according to the elevator load; and reallocating the service range for the elevator group when overload occurs; When the energy storage power supply mode is triggered, the method for aggregating continuous high-demand areas to form a merged layer through destination floor data is as follows: a destination floor historical data set is intercepted from the destination floor data in real time; the destination floor historical data set is composed of a number of destination floor historical data records, each destination floor historical data record includes a real-time timestamp distance and a destination floor, and the real-time timestamp distance value range is 10 to 60 minutes; The DBSCAN clustering method is used to cluster the historical data set of the destination floors. The clustering results are filtered by the LOF algorithm to obtain several clusters. The cluster with the largest number of elements is the target cluster. All target floors are identified from the target cluster, and any set of consecutive target floors is recorded as a merged layer. The method for judging whether the service scope of an elevator is overloaded according to its load is as follows: the feedback interval is preset to be 2 seconds to 20 seconds, and the time point corresponding to each feedback interval is recorded as a monitoring point. The elevator load includes the power consumption value and the power peak value obtained once at each monitoring point, wherein the power consumption value is the average power consumption in the dynamic window corresponding to the monitoring point. The imbalance factor set is obtained according to the power consumption value and the power peak value. If the imbalance factor of each elevator in its imbalance factor set meets the Z-Score ≥ 2.5, it is determined that the elevator is overloaded, and the overloaded elevator is pointed to the elevator corresponding to the maximum value in the imbalance factor set; The method for reallocating the service range for the elevator group when overload occurs is: select and define the elevator when overload occurs as the re-planned elevator, and its service range is a floor range composed of several consecutive floors, which is recorded as a service floor set, and the highest floor in the service floor set is eliminated.

2. The method for adaptively splitting elevator traffic using a combined floor strategy with emergency power supply according to claim 1 is characterized in that: The method of identifying the energy storage power supply mode by monitoring the elevator voltage fluctuation is: use a voltage sensor to collect the elevator voltage data in real time, set the dynamic window to 2 to 10 minutes; obtain the average value of each voltage data in the dynamic window at each moment and record it as the window voltage, fit each window voltage through a curve and obtain the change rate of the curve at each moment and record it as the voltage-sharing change rate; if the voltage-sharing change rate is greater than the preset voltage-changing threshold, it is identified that the energy storage power supply mode is turned on.

3. The method for adaptively splitting elevator traffic using a combined floor strategy and powered by an emergency power supply according to claim 1 is characterized in that: The method of identifying the energy storage power supply mode by monitoring the elevator voltage fluctuation is: use a voltage sensor to collect the elevator voltage data in real time, set the dynamic window to 2 to 10 minutes, and when the voltage data fluctuates within the dynamic window by more than ±5%, it is identified that the energy storage power supply mode is turned on.

4. The method for adaptively splitting elevator traffic using a combined floor strategy powered by an emergency power supply according to claim 1 is characterized in that: The method for obtaining the imbalance factor set according to the power consumption value and the power peak value is as follows: when judging whether the service scope of the elevator is overloaded according to the elevator load, a quantile-driven discretization strategy is used to divide the parameter space of the power consumption and the power peak into four interval units respectively, and ensure that the probability density distribution of each interval satisfies the non-uniformity constraint; the range of the power consumption value in the interval unit is the range amplitude, and the median value of the power consumption value is the robust central estimator; the median value of the power peak value is the typical characterization quantity; the power consumption weight of the interval unit is the normalized ratio of its range amplitude to the sum of the range amplitudes of all interval units; the power weight of the interval unit is the ratio of its typical characterization quantity to the sum of the typical characterization quantities of all interval units; a hyperbolic tangent function is constructed through the power weight and the range amplitude to obtain the imbalance factor; the set of all imbalance factors between the last maintenance of the elevator and the current one is recorded as the imbalance factor set.

5. The method for adaptively splitting elevator traffic using a combined floor strategy and powered by an emergency power supply according to claim 1 is characterized in that: The method of obtaining the imbalance factor set according to the power consumption value and the power peak value is as follows: the independent variables σ of the power consumption value and the power peak value are T , σ P Based on, define the parameter load discrete level R TP The parameter load discrete level is used to characterize the intrinsic reflection of the synergistic relationship between power consumption and power peak on the dynamic sensitivity of the system load; the first load discrimination model is constructed by examining the change behavior of the load discrete level over time; the second load discrimination model describing the elevator load is constructed according to the first load discrimination model to obtain the imbalance factor; the set of all imbalance factors between the last elevator maintenance and the current one is recorded as the imbalance factor set.

6. An emergency power supply-powered elevator adaptive diversion system with a combined floor strategy, characterized in that: The adaptive diversion system for elevators with a merged layer strategy powered by an emergency power supply comprises: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the adaptive diversion method for elevators with a merged layer strategy powered by an emergency power supply are implemented as described in any one of claims 1 to 5. The adaptive diversion system for elevators with a merged layer strategy powered by an emergency power supply runs on computing devices such as desktop computers, laptop computers, PDAs, and cloud data centers.

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